Add configuration files for FastGPT and Xfyun voice services, enhancing LLM service capabilities. Update LLMConfig to include chat_id, variables, detail, and timeout settings. Refactor create_llm_service to support FastGPT integration and adjust pipeline to handle chat_id and greeting prompts. Implement context synchronization for interrupted assistant turns in text streaming.

src/voice/config.py

@@ -107,6 +107,11 @@ class LLMConfig:
     base_url: str | None = None
     model: str = "gpt-4o-mini"
     temperature: float | None = 0.7
+    chat_id: str | None = None
+    variables: dict[str, str] = field(default_factory=dict)
+    detail: bool = False
+    timeout_sec: float = 60.0
+    send_system_prompt: bool = False
 
 
 @dataclass(frozen=True)
@@ -183,6 +188,12 @@ def config_from_dict(data: dict) -> EngineConfig:
     if stt.get("language") == "":
         stt["language"] = None
 
+    llm = _dict(services.get("llm"))
+    if llm.get("chat_id") == "":
+        llm["chat_id"] = None
+    if not isinstance(llm.get("variables"), dict):
+        llm["variables"] = {}
+
     turn = _dict(data.get("turn"))
     vad = _dict(turn.get("vad"))
 
@@ -210,7 +221,7 @@ def config_from_dict(data: dict) -> EngineConfig:
         ),
         agent=AgentConfig(**agent),
         services=ServicesConfig(
-            llm=LLMConfig(**_dict(services.get("llm"))),
+            llm=LLMConfig(**llm),
             stt=STTConfig(**stt),
             tts=TTSConfig(**_dict(services.get("tts"))),
         ),